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Knowledge library

Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.

Quant Q&A
20,364 documents
SuperMind
12,226 documents
OKX Learn
8,431 documents
Strategy library
7,910 documents
MQL5 code base
7,090 documents
BigQuant
3,481 documents
Bitget Academy
3,298 documents
MQL5 articles
3,012 documents
TradingView scripts
1,976 documents
ProRealCode
1,507 documents
Deribit Insights
1,232 documents
Machine Learning for Trading
1,124 documents
arXiv papers
1,033 documents
Amberdata research
766 documents
FMZ forum
682 documents
FMZ digest
662 documents
vn.py community
560 documents
QuantInsti blog
511 documents
Galaxy Research
340 documents
QuantStart
246 documents
Stratmill research code
219 documents
Robot Wealth
195 documents
NautilusTrader
191 documents
Hummingbot docs
181 documents
Paradigm research
175 documents
Lumibot
164 documents
Kraken Learn
163 documents
Quant course library
157 documents
OctoBot
152 documents
Cryptohopper blog
144 documents
Systematic trading blog (Rob Carver)
132 documents
Qlib
116 documents
Quantpedia
86 documents
TqSdk
86 documents
Hyperliquid docs
79 documents
Freqtrade
68 documents
Hudson & Thames
62 documents
Awesome Systematic Trading
61 documents
backtrader
54 documents
vn.py
50 documents
Quantopian lectures
45 documents
Binance API docs
45 documents
FMZ guides
38 documents
pysystemtrade
34 documents
Freqtrade docs
32 documents
quant-trading
31 documents
FinRL
28 documents
Zipline
22 documents
FMZ live strategies
21 documents
Jesse
17 documents
pyfolio
16 documents
Alphalens
14 documents
WonderTrader
14 documents
backtesting.py
11 documents
Technical Analysis
9 documents
QTPyLib
8 documents
QuantRocket
7 documents
Lumibot strategies
7 documents
Awesome Quant
1 documents

Search the library

12,303 documents

SuperMind

This stock-selection method combines three daily conditions: prior-session amplitude above 1%, an opening price within 5% of the 10-day moving average, and prior-day turnover above 8%. It is intended to find shares with notable price movement, an opening…

EquitiesTechnical indicatorsVolatility
SuperMind

This note describes a simple equity screen for stocks whose codes begin with 60, whose daily high-to-low range exceeds 1% of the prior close, and whose turnover rate is between 3% and 12%. It presents the criteria as indicators of price movement and trading…

EquitiesChina marketsVolatilityTechnical indicators
MQL5 code base

The document describes Average Percentage True Range (APTR), a volatility indicator attributed to a 2015 magazine article. It first calculates a percentage true-range value for each period using the high, low, and previous close, then applies a simple moving…

Technical indicatorsVolatilityStatistics
MQL5 code base

The document describes a QQE-style indicator that combines a smoothed RSI with fast and slow volatility-based trailing levels. It says the version uses RSX, a smoother RSI variant, as its momentum input, and adds fixed reference levels to help estimate trend…

Technical indicatorsMomentumTrend followingVolatility
SuperMind

This stock-screening idea selects shares whose daily high-to-low range exceeds one percent, that have had at least one limit-up session during the previous 25 days, and whose current opening-auction change falls between minus two and five percent. The post…

EquitiesChina marketsTechnical indicatorsVolatility
Amberdata research

This episode recap discusses crypto market structure, macroeconomic themes, and options positioning across Bitcoin, Ethereum, and Solana. It describes subdued sentiment alongside recovering prices, contrasts crypto with equities and gold, and presents the…

CryptoOptionsVolatilitySentiment
Amberdata research

The document introduces crypto calls and puts, explaining the buyer’s rights and the seller’s obligations. It describes moneyness by comparing the strike with the underlying price, and outlines intrinsic value and time value. It also introduces delta, gamma,…

CryptoOptionsDerivatives pricingVolatility
Amberdata research

This weekly recap describes conditions in BTC and ETH options around a major BTC expiry. It reports that BTC realized volatility had declined, with seven-day realized volatility returning to the 30s. The term structures changed little: front-end volatility…

CryptoOptionsVolatilityDerivatives pricing
ProRealCode

The document explains Rolling VWAP as a continuously updated volume-weighted average over a recent window of bars, unlike a conventional VWAP that resets daily. Its calculation divides the sum of each selected price multiplied by volume by total volume. A…

Technical indicatorsStatisticsVolatilityBacktesting
MQL5 code base

Range Rider compares a fast moving average of true range with a slower one, expressing the ratio as a percentage. The indicator is attributed to Larry Williams. Its purpose is to highlight periods when the price range is contracting; such compression may…

Technical indicatorsVolatility
BigQuant

The KCI indicator combines four price-derived measures: average price velocity, deviation from a local moving average, rolling price dispersion, and the change in velocity. The document proposes normalizing each measure with a rolling Z-score and combining…

Technical indicatorsMean reversionVolatilityRisk management
MQL5 code base

This document describes a simple volatility display that measures candlestick size and shows the result as a histogram in a separate chart window. A user-set threshold, expressed in points, determines the color: bars above it appear purple, while bars at or…

VolatilityTechnical indicators
SuperMind

This document outlines a stock selection approach using daily price amplitude above 1, a positive weekly MACD histogram, and an arc-shaped price pattern. It interprets the amplitude condition as a volatility filter, the weekly indicator as evidence of upward…

EquitiesTechnical indicatorsVolatilityMomentum
Amberdata research

This report reviews Ethereum market and ecosystem developments across early 2025, linking price weakness and volatility to macroeconomic pressure, a major exchange hack, institutional ETF positioning, staking yields, and network upgrades. It describes…

CryptoOn-chain dataSentimentVolatility
SuperMind

This proposed stock screen combines a daily high-low amplitude threshold, prior-day turnover between 3% and 28%, and an upward arrangement of the 5-, 10-, and 20-day moving averages. The short and medium averages must exceed the longer average, while the 5-…

EquitiesTechnical indicatorsTrend followingVolatility
ProRealCode

This indicator marks unusually high volume directly on a price chart. It compares each bar’s volume with percentile thresholds across short, medium, and long lookback windows of 20, 50, and 100 bars. The three cluster levels identify the upper 25%, 10%, and…

Technical indicatorsStatisticsMarket microstructureBreakout
SuperMind

This note presents an equity screen combining daily price range, a 2021 date filter, and a recent large gain. It describes selecting stocks whose high-to-low range exceeds 1% of the previous close and that had a daily gain of at least 10% within the prior 25…

EquitiesVolatilityMomentumTechnical indicators
Awesome Systematic Trading

The document implements a monthly long-only stock-selection approach based on historical volatility. It describes ranking large-cap stocks by the volatility of weekly returns over roughly three years, then holding an equally weighted group from the…

EquitiesFactor investingVolatilityPortfolio construction
MQL5 code base

The document briefly describes a step-channel indicator whose underlying volatility measure is a 70-period moving average of a 10-period standard deviation. An update note says a hybrid mode was added. It recommends using two step channels and includes…

VolatilityTechnical indicators
SuperMind

The document describes a stock screen intended to find active shares that may be attracting market attention. Its stated rules require price amplitude above 1, previous-day turnover above 8%, and a product of previous-day turnover and the ratio of today’s…

EquitiesChina marketsTechnical indicatorsVolatility
Amberdata research

This market review examines crypto options and volatility during the sharp January 2023 rally. It connects the post-inflation-data rise in Bitcoin and Ether with higher realized and implied volatility, a backwardated Bitcoin volatility term structure, and…

CryptoOptionsVolatilityMarket microstructure
MQL5 code base

The described expert advisor combines two moving averages with a standard deviation indicator. Its stated sell setup requires the fast moving average to be below the slow one, the preceding candle to be bearish and close below the fast average, and standard…

Technical indicatorsVolatilityRisk management
vn.py community

This event outline introduces options volatility trading through pricing theory, portfolio profit and loss, and the role of delta hedging. It distinguishes historical volatility, implied volatility as reflected in option time value, and realized volatility…

OptionsVolatilityDerivatives pricingRisk management
Amberdata research

This weekly digital asset report combines price and volume changes with derivatives positioning, orderbook liquidity, institutional flows, stablecoin supply, and DeFi activity. It interprets the reported pullback as consolidation after a rally: open interest…

CryptoPerpetual futuresMarket microstructureSentiment